Sentiment, Readability, and Disclosure Quality in Corporate Financial Reporting: A Textual and Behavioral Perspective on Market Information Efficiency

Abstract

Corporate financial reporting has evolved from a predominantly numerical disclosure system into a complex narrative-driven communication mechanism where textual content plays a decisive role in shaping investor perception, market reactions, and information efficiency. This study develops an extensive theoretical and empirical synthesis of how sentiment, readability, and disclosure quality embedded within corporate financial reports influence capital market outcomes. Drawing strictly from established literature on textual analysis, sentiment mining, disclosure adequacy, regulatory filings, and behavioral finance, the article examines the informational role of narrative disclosures such as annual reports, SEC filings, earnings communications, and voluntary textual supplements. By integrating classical disclosure theory with modern text analytics and deep learning-based sentiment extraction, this research bridges early foundational disclosure studies with contemporary computational approaches. The article elaborates on how linguistic tone, complexity, and structure affect stock return synchronicity, analyst behavior, investor attention, and fraud detection. It also critically evaluates the implications of digital reporting formats such as XBRL and multimodal disclosures that combine textual and vocal sentiment. Through an in-depth descriptive methodology, the findings reveal that textual characteristics are not merely stylistic artifacts but function as economically meaningful signals that shape capital allocation decisions, corporate transparency, and governance outcomes. The discussion highlights theoretical tensions between information overload and informativeness, managerial discretion versus market discipline, and technological sophistication versus interpretive bias. Limitations related to context dependency, linguistic ambiguity, and regulatory heterogeneity are explored in detail, alongside future research directions focusing on cross-country disclosure regimes and ethical considerations in automated text interpretation. This study contributes to accounting, finance, and information systems literature by offering a unified, deeply elaborated framework for understanding narrative financial disclosure as a central pillar of modern market information architecture.